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Option to use a smaller model for faster computation #20
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This sounds like a good plan to me. A few things to note:
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I'm inclined to downloading all models from GH if possible, because including the same model for every release is a waste/abuse of PyPI storage.
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OK, sounds good. Let me know if you need my help with any of this, cheers. |
jongwook
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Currently the model capacity multiplier is fixed to 32, but this can be adjusted as a trade-off between the computation time and accuracy. Roughly speaking, the number of parameters is quadratic to this multiplier.
The one that is deployed on https://marl.github.io/crepe uses model multiplier 4, and still achieves quite comparable performance:
(note that these numbers are on MedleyDB v1 and not comparable to what's reported in the paper)
We'd like to have an option to select a smaller model, for faster calculation in the cost of slightly lower accuracy.
I'd suggest the following options for specifying the model capacity.
--model-capacity full
--model-capacity large
--model-capacity medium
--model-capacity small
--model-capacity tiny
Currently the size of the PyPI archive is 57.7 MB, very close to the 60 MB limit, and it's only possible to add the
tiny
for immediate upload to PyPI. Requesting quota increase on PyPI is possible, but it seems quite difficult and not so sure if they will allow us the increase.We can alternatively put the models on a separate branch in this repo, and have the code download the models during the installation or first use.
Let me do the former first (adding
tiny
), and figure out how to add the other three later.The text was updated successfully, but these errors were encountered: